Friday, February 26, 2010

Darren Herman's article on AdExchanger this week is more important than it might seem at first read: it's the first time a major figure in our little adtech industry has pointed out that what we've built in terms of exchanges and platforms and data is just a small first step to what we will need to build over the next decade. Bear with me.

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1. The state of the state

Those of you who have been reading this blog for the past year know I've been thinking about several online display advertising paradoxes:

The first internet marketing rant I heard was "the internet will create true one-to-one, accountable, ROI driven marketing!" That was in 1995.

Still waiting.

But it's true, or will be some day. The ability to dynamically maximize the ROI of your campaigns across all media in real-time is what our industry is building. To do this we need to be able to formulate hypotheses, test them, figure out the ROI, and reallocate into the highest ROI buys. And then, because humans are changeable beasts, we need to do it all over again, forever.

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3. What is Quality?

ROI is the value of the customer divided by the cost of acquiring them.

ROI = LTV / CPA

Computing this isn't as simple as it sounds.

Back in the day, at Prodigy, we kept track of each customer by when they started and by what marketing channel they arrived. For each marketing channel we would track the average lifecycle. That is, for a customer arriving in month x, 80% would stay one month (first month was free!), 40% would stay two months, 30% three months, 25% four months, etc.* The churn was different by marketing campaign because some campaigns got people for whom the product was wrong to sign up: they did not stay long.

We then multiplied the probability that any given person would remain in a given month by their contribution margin for that month (say $10, except in the free trial month, when it was -$10) and discounted all that back to month 0 using the company's cost of capital**. This was the customer lifetime value (LTV).

This is a complicated example. If you are promoting an offer where you get paid $2 every time you bring someone a customer, your LTV for that customer is, essentially, $2. But in most cases, the right customers are more likely to remain customers (unless you subsequently scare them away), and the wrong customers are less likely to remain customers, so the LTV is usually dependent on the marketing campaign.

Now, to the cost of acquiring a customer using display advertising. This part most of you know. I'm going to do it the simplest way, though.

CPA = Cost of media x Conversion = CPM/1000 x Conversion

Conversion here is number of people who see the ad divided by the number of people who become customers of the advertiser. That is, they convert from ad viewer to customer. Conversion is key, but it is an incredibly complicated thing to predict because it depends on: who the viewer is, what they are thinking at that moment, what they are looking to buy, where and when they are seeing the ad, what surrounds the ad, how many times they have seen the ad before, what the ad itself is, whether they are interested in what is being advertised, etc.

ROI = LTV /(CPM/1000 x Conversion)

None of LTV, CPM and Conversion are independent of the others, each depends on the particulars of the campaign (i.e. targeting high-net worth individuals changes CPMs , changes conversion, and changes LTV, the latter two in ways depending on the product.)

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4. What are we doing now?

What we measure now in the adtech industry is CPM. Some DSPs, with some clients, will claim that they are doing more. But if there is true integration of conversion into their buys--or any integrations that go much beyond "the CMO likes the results"--then it is extremely rare.

Because the adtech people can't measure conversion*** or LTV, they optimize CPM while trying to hold LTV and conversion constant. Using the same creative and target viewer, they find lower CPMs. This explains the puzzles I mention above.

There isn't more eyeball time (i.e. supply), but we are putting ads in places that previously had no ads. On social networking sites, on UGC sites, on small sites, etc. We do this by using targeting data to find the few "right" viewers in the sea of "wrong" viewers. There isn't more attention to sell, we are just selling more ads per hour of attention. This is the increase in supply. (I mentioned this previously.)

People do not see "lift" (i.e. increase in the conversion rate) by using targeting data because that's not what we are using it for. We are using targeting data to increase reach and find the same conversion rates at a lower CPM. Targeting data increases ROI by lowering CPMs, not increasing conversion.

If CPMs are falling at the major media purveyors (as reported) then that is being made up for by increasing CPMs on social networks, etc. On average CPMs are not falling, but there is an equalization of CPMs happening across internet media. We hear the lament of the New York Times' of the world, but not the jubilation of everyone else. Facebook's ad revenue came not entirely by taking time spent with the NYTimes away, it also came by lowering their CPMs. You can find the same person you were targeting at the NYTimes on Facebook, for lower cost.

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5. What's next?

This is a great service to marketers. Adtech increases ROI. But it's transitory. Once enough ad dollars use a specific way of finding the right viewer on overlooked sites, the price of the inventory on those sites rises. We are right-pricing all the inventory on the internet after years of it being overpriced on the high-profile sites and underpriced everywhere else.

But there are declining returns to this strategy, as the inventory becomes more rationally priced. I've heard some rumblings to this effect already, although I think we have another couple of years before it becomes widespread.

Step two is to focus on conversion. This is what Darren was implying in his article. But to know conversion, there has to be integration back into the marketer: did this particular instance of an ad result in a product being sold? When this feedback loop is in place****, marketer's agents can start to use the algorithms they used to find low CPMs to find higher conversion rates. This will be a sea-change. But implementing it will be difficult because it requires substantial tech investment at the marketer, as well as procedural and probably cultural change. It's also one of the primary reasons the DSPs will have to choose between being a marketer's agent--working directly with marketers--or a technology provider to marketer's agents.

Step two is now. If you are starting a company to do this, contact me.

Kotler spends less than 5% of his seminal textbook on advertising, the rest is about customer value, loyalty, product strategy, pricing, etc. But in the adtech world, it's all about advertising/direct marketing/promotion. When we can measure the effect of marketing communications on LTV, that will change.

Increasing LTV means keeping customers, not getting them. It means figuring out what customers want and building or changing your product to keep them. It means finding the right pricing, providing the right customer service and out-innovating your competitors.

And that is the holy grail of marketing.

-------* These numbers are illustrative, but directionally correct. I don't remember the real numbers. It's been a long time.** I don't really want to explain contribution margin, discounting and cost of capital. This post is going to be long enough as it is. Ask Fred Wilson on Monday.*** Click-through is not conversion. If you've ever been in lead-gen you know you can easily and cheaply generate poor quality click-through. Free i-pod, anyone?**** Outside of the arbitrage world, where it is being done now. The arbitragers are and always have been the smartest people in marketing.

good post and definitely agree with you with regards to direct-marketing campaigns and any product/service where you can measure LTV. However, once you move outside of that realm (say consumer goods, luxury, brand advertisers) it gets harder - how do you define LTV for them? I'm seeing more brands go in the direction of creating "A" as in CPA on their sites - be it sweeps, reg forms or other events to get closer to an LTV. Definitely true that a "flattening" of CPMs is taking place though and the "premium" sites are suffering from it.

Christian-- Figuring LTV for goods that are brand-advertised is tough. But one of the two reasons we brand is to increase customer loyalty (the other is to get them to feel good paying more, sigh). If we spend money increasing customer loyalty, then we should have some rationale behind spending it.

I agree this is hard, and will probably be open to charges of subjectivism once implemented. But the stuff we're doing today in data-targeted advertising would have been derided as pretty far-fetched a decade ago too.

Very interesting post Jerry. A couple of thoughts. Remarketing is one example where data can work. Banner ads that retarget your own site visitors generally deliver a workable ROI. IMO data transparency is critical in knowing it's value. There is good data and bad data. Buying data blindly is like buying an impression blindly.

Last click/view attribution is an innacurate measure of results and really needs to move forward. Closing the loop has never been easy and it seems to me it will only get harder to measure as more touchpoints and media devices/outlets come to market.